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<a href="#pub-types">Public 类型</a> &#124;
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<div class="title">pcl::gpu::EuclideanClusterExtraction类 参考</div>  </div>
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<p><b><a class="el" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html" title="EuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sen...">EuclideanClusterExtraction</a></b> represents a segmentation class for cluster extraction in an Euclidean sense, depending on pcl::gpu::octree  
 <a href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#details">更多...</a></p>

<p><code>#include &lt;<a class="el" href="gpu__extract__clusters_8h_source.html">gpu_extract_clusters.h</a>&gt;</code></p>
<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-types"></a>
Public 类型</h2></td></tr>
<tr class="memitem:afca1a1224d998622283e08cac8f3a7e8"><td class="memItemLeft" align="right" valign="top"><a id="afca1a1224d998622283e08cac8f3a7e8"></a>
typedef <a class="el" href="structpcl_1_1_point_x_y_z.html">pcl::PointXYZ</a>&#160;</td><td class="memItemRight" valign="bottom"><b>PointType</b></td></tr>
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<tr class="memitem:accf22afc0603dfef6f2dba9f65ded746"><td class="memItemLeft" align="right" valign="top"><a id="accf22afc0603dfef6f2dba9f65ded746"></a>
typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z.html">pcl::PointXYZ</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudHost</b></td></tr>
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typedef PointCloudHost::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudHostPtr</b></td></tr>
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typedef PointCloudHost::ConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudHostConstPtr</b></td></tr>
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typedef PointIndices::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>PointIndicesPtr</b></td></tr>
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typedef PointIndices::ConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointIndicesConstPtr</b></td></tr>
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typedef <a class="el" href="classpcl_1_1gpu_1_1_octree.html">pcl::gpu::Octree</a>&#160;</td><td class="memItemRight" valign="bottom"><b>GPUTree</b></td></tr>
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typedef <a class="el" href="classpcl_1_1gpu_1_1_octree.html#aaef633c03e07b4ccf653afa6f314be75">pcl::gpu::Octree::Ptr</a>&#160;</td><td class="memItemRight" valign="bottom"><b>GPUTreePtr</b></td></tr>
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typedef <a class="el" href="classpcl_1_1gpu_1_1_octree.html#a2584f9e71b717c8c891415199661a2c3">pcl::gpu::Octree::PointCloud</a>&#160;</td><td class="memItemRight" valign="bottom"><b>CloudDevice</b></td></tr>
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Public 成员函数</h2></td></tr>
<tr class="memitem:aada2788e50b364ccbb97e6850d1af3c3"><td class="memItemLeft" align="right" valign="top"><a id="aada2788e50b364ccbb97e6850d1af3c3"></a>
&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#aada2788e50b364ccbb97e6850d1af3c3">EuclideanClusterExtraction</a> ()</td></tr>
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<tr class="memitem:a95c549e9549f86d19df8abfbcac0add6"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a95c549e9549f86d19df8abfbcac0add6">setSearchMethod</a> (GPUTreePtr &amp;tree)</td></tr>
<tr class="memdesc:a95c549e9549f86d19df8abfbcac0add6"><td class="mdescLeft">&#160;</td><td class="mdescRight">the destructor  <a href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a95c549e9549f86d19df8abfbcac0add6">更多...</a><br /></td></tr>
<tr class="separator:a95c549e9549f86d19df8abfbcac0add6"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a4517e73e5d5530cf69d1e1a5f8ca6918"><td class="memItemLeft" align="right" valign="top">GPUTreePtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a4517e73e5d5530cf69d1e1a5f8ca6918">getSearchMethod</a> ()</td></tr>
<tr class="memdesc:a4517e73e5d5530cf69d1e1a5f8ca6918"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the search method used.  <a href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a4517e73e5d5530cf69d1e1a5f8ca6918">更多...</a><br /></td></tr>
<tr class="separator:a4517e73e5d5530cf69d1e1a5f8ca6918"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a292d2bc70907745884b5e15a7ffd61f4"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a292d2bc70907745884b5e15a7ffd61f4">setClusterTolerance</a> (double tolerance)</td></tr>
<tr class="memdesc:a292d2bc70907745884b5e15a7ffd61f4"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the spatial cluster tolerance as a measure in the L2 Euclidean space  <a href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a292d2bc70907745884b5e15a7ffd61f4">更多...</a><br /></td></tr>
<tr class="separator:a292d2bc70907745884b5e15a7ffd61f4"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a4c4f9e524544756743f03d5c86ef92e1"><td class="memItemLeft" align="right" valign="top"><a id="a4c4f9e524544756743f03d5c86ef92e1"></a>
double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a4c4f9e524544756743f03d5c86ef92e1">getClusterTolerance</a> ()</td></tr>
<tr class="memdesc:a4c4f9e524544756743f03d5c86ef92e1"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the spatial cluster tolerance as a measure in the L2 Euclidean space. <br /></td></tr>
<tr class="separator:a4c4f9e524544756743f03d5c86ef92e1"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a232fc7f0877a4dd40131471f1c8164b6"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a232fc7f0877a4dd40131471f1c8164b6">setMinClusterSize</a> (int min_cluster_size)</td></tr>
<tr class="memdesc:a232fc7f0877a4dd40131471f1c8164b6"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the minimum number of points that a cluster needs to contain in order to be considered valid.  <a href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a232fc7f0877a4dd40131471f1c8164b6">更多...</a><br /></td></tr>
<tr class="separator:a232fc7f0877a4dd40131471f1c8164b6"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a749098361f3494516e1932a65a079279"><td class="memItemLeft" align="right" valign="top"><a id="a749098361f3494516e1932a65a079279"></a>
int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a749098361f3494516e1932a65a079279">getMinClusterSize</a> ()</td></tr>
<tr class="memdesc:a749098361f3494516e1932a65a079279"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the minimum number of points that a cluster needs to contain in order to be considered valid. <br /></td></tr>
<tr class="separator:a749098361f3494516e1932a65a079279"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7e03de53c8b6b1e8e43454177da35eba"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a7e03de53c8b6b1e8e43454177da35eba">setMaxClusterSize</a> (int max_cluster_size)</td></tr>
<tr class="memdesc:a7e03de53c8b6b1e8e43454177da35eba"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the maximum number of points that a cluster needs to contain in order to be considered valid.  <a href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a7e03de53c8b6b1e8e43454177da35eba">更多...</a><br /></td></tr>
<tr class="separator:a7e03de53c8b6b1e8e43454177da35eba"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3afe1ecff86b57489025736d69548111"><td class="memItemLeft" align="right" valign="top"><a id="a3afe1ecff86b57489025736d69548111"></a>
int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a3afe1ecff86b57489025736d69548111">getMaxClusterSize</a> ()</td></tr>
<tr class="memdesc:a3afe1ecff86b57489025736d69548111"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the maximum number of points that a cluster needs to contain in order to be considered valid. <br /></td></tr>
<tr class="separator:a3afe1ecff86b57489025736d69548111"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a814a134ff5baf8271bae14a8b62e23a3"><td class="memItemLeft" align="right" valign="top"><a id="a814a134ff5baf8271bae14a8b62e23a3"></a>
void&#160;</td><td class="memItemRight" valign="bottom"><b>setInput</b> (<a class="el" href="classpcl_1_1gpu_1_1_device_array.html">CloudDevice</a> input)</td></tr>
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void&#160;</td><td class="memItemRight" valign="bottom"><b>setHostCloud</b> (PointCloudHostPtr host_cloud)</td></tr>
<tr class="separator:ab493f28f7dfec4f5cd4c6f7ebf3423aa"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa26c2aa71ba074f4083bb784e8b3c142"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#aa26c2aa71ba074f4083bb784e8b3c142">extract</a> (std::vector&lt; <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &gt; &amp;clusters)</td></tr>
<tr class="memdesc:aa26c2aa71ba074f4083bb784e8b3c142"><td class="mdescLeft">&#160;</td><td class="mdescRight">Cluster extraction in a <a class="el" href="classpcl_1_1_point_cloud.html" title="PointCloud represents the base class in PCL for storing collections of 3D points.">PointCloud</a> given by &lt;setInputCloud (), setIndices ()&gt;  <a href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#aa26c2aa71ba074f4083bb784e8b3c142">更多...</a><br /></td></tr>
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</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pro-methods"></a>
Protected 成员函数</h2></td></tr>
<tr class="memitem:abb1604d5c5d76a8f312dbe43e948464c"><td class="memItemLeft" align="right" valign="top"><a id="abb1604d5c5d76a8f312dbe43e948464c"></a>
virtual std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#abb1604d5c5d76a8f312dbe43e948464c">getClassName</a> () const</td></tr>
<tr class="memdesc:abb1604d5c5d76a8f312dbe43e948464c"><td class="mdescLeft">&#160;</td><td class="mdescRight">Class getName method. <br /></td></tr>
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</table><table class="memberdecls">
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Protected 属性</h2></td></tr>
<tr class="memitem:a7696e24ea2501da78eea60b1a5f53110"><td class="memItemLeft" align="right" valign="top"><a id="a7696e24ea2501da78eea60b1a5f53110"></a>
<a class="el" href="classpcl_1_1gpu_1_1_device_array.html">CloudDevice</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a7696e24ea2501da78eea60b1a5f53110">input_</a></td></tr>
<tr class="memdesc:a7696e24ea2501da78eea60b1a5f53110"><td class="mdescLeft">&#160;</td><td class="mdescRight">the input cloud on the GPU <br /></td></tr>
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PointCloudHostPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a21dd4fdd0c79869c78c592cc5c1fe621">host_cloud_</a></td></tr>
<tr class="memdesc:a21dd4fdd0c79869c78c592cc5c1fe621"><td class="mdescLeft">&#160;</td><td class="mdescRight">the original cloud the Host <br /></td></tr>
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GPUTreePtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#afa283395168a4d277abf9190c9d536aa">tree_</a></td></tr>
<tr class="memdesc:afa283395168a4d277abf9190c9d536aa"><td class="mdescLeft">&#160;</td><td class="mdescRight">A pointer to the spatial search object. <br /></td></tr>
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<tr class="memitem:a6b53d0688720222882181e18967ca731"><td class="memItemLeft" align="right" valign="top"><a id="a6b53d0688720222882181e18967ca731"></a>
double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a6b53d0688720222882181e18967ca731">cluster_tolerance_</a></td></tr>
<tr class="memdesc:a6b53d0688720222882181e18967ca731"><td class="mdescLeft">&#160;</td><td class="mdescRight">The spatial cluster tolerance as a measure in the L2 Euclidean space. <br /></td></tr>
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int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a81a359b0267f431fe49e3a8ce69548b7">min_pts_per_cluster_</a></td></tr>
<tr class="memdesc:a81a359b0267f431fe49e3a8ce69548b7"><td class="mdescLeft">&#160;</td><td class="mdescRight">The minimum number of points that a cluster needs to contain in order to be considered valid (default = 1). <br /></td></tr>
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int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#ac16cba791c7693efe0c0f62ca753d775">max_pts_per_cluster_</a></td></tr>
<tr class="memdesc:ac16cba791c7693efe0c0f62ca753d775"><td class="mdescLeft">&#160;</td><td class="mdescRight">The maximum number of points that a cluster needs to contain in order to be considered valid (default = MAXINT). <br /></td></tr>
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<a name="details" id="details"></a><h2 class="groupheader">详细描述</h2>
<div class="textblock"><p><b><a class="el" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html" title="EuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sen...">EuclideanClusterExtraction</a></b> represents a segmentation class for cluster extraction in an Euclidean sense, depending on pcl::gpu::octree </p>
<dl class="section author"><dt>作者</dt><dd>Koen Buys, Radu Bogdan Rusu </dd></dl>
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<h2 class="memtitle"><span class="permalink"><a href="#aa26c2aa71ba074f4083bb784e8b3c142">&#9670;&nbsp;</a></span>extract()</h2>

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          <td class="memname">void pcl::gpu::EuclideanClusterExtraction::extract </td>
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          <td class="paramtype">std::vector&lt; <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &gt; &amp;&#160;</td>
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<p>Cluster extraction in a <a class="el" href="classpcl_1_1_point_cloud.html" title="PointCloud represents the base class in PCL for storing collections of 3D points.">PointCloud</a> given by &lt;setInputCloud (), setIndices ()&gt; </p>
<dl class="params"><dt>参数</dt><dd>
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    <tr><td class="paramname">clusters</td><td>the resultant point clusters </td></tr>
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<div class="fragment"><div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;{</div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;<span class="comment">/*</span></div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;<span class="comment">  // Initialize the GPU search tree</span></div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;<span class="comment">  if (!tree_)</span></div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;<span class="comment">  {</span></div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;<span class="comment">    tree_.reset (new pcl::gpu::Octree());</span></div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;<span class="comment">    tree_.setCloud(input_);</span></div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;<span class="comment">  }</span></div>
<div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;<span class="comment">*/</span></div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;  <span class="keywordflow">if</span> (!<a class="code" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#afa283395168a4d277abf9190c9d536aa">tree_</a>-&gt;isBuilt())</div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;  {</div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;    <a class="code" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#afa283395168a4d277abf9190c9d536aa">tree_</a>-&gt;build();</div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;  }</div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;<span class="comment">/*</span></div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;<span class="comment">  if(tree_-&gt;cloud_.size() != host_cloud.points.size ())</span></div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;<span class="comment">  {</span></div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;<span class="comment">    PCL_ERROR(&quot;[pcl::gpu::EuclideanClusterExtraction] size of host cloud and device cloud don&#39;t match!\n&quot;);</span></div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;<span class="comment">    return;</span></div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;<span class="comment">  }</span></div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;<span class="comment">*/</span></div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;  <span class="comment">// Extract the actual clusters</span></div>
<div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;  extractEuclideanClusters (<a class="code" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a21dd4fdd0c79869c78c592cc5c1fe621">host_cloud_</a>, <a class="code" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#afa283395168a4d277abf9190c9d536aa">tree_</a>, <a class="code" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a6b53d0688720222882181e18967ca731">cluster_tolerance_</a>, clusters, <a class="code" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a81a359b0267f431fe49e3a8ce69548b7">min_pts_per_cluster_</a>, <a class="code" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#ac16cba791c7693efe0c0f62ca753d775">max_pts_per_cluster_</a>);</div>
<div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;  std::cout &lt;&lt; <span class="stringliteral">&quot;INFO: end of extractEuclideanClusters &quot;</span> &lt;&lt; std::endl;</div>
<div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;  <span class="comment">// Sort the clusters based on their size (largest one first)</span></div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;  <span class="comment">//std::sort (clusters.rbegin (), clusters.rend (), comparePointClusters);</span></div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;}</div>
<div class="ttc" id="aclasspcl_1_1gpu_1_1_euclidean_cluster_extraction_html_a21dd4fdd0c79869c78c592cc5c1fe621"><div class="ttname"><a href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a21dd4fdd0c79869c78c592cc5c1fe621">pcl::gpu::EuclideanClusterExtraction::host_cloud_</a></div><div class="ttdeci">PointCloudHostPtr host_cloud_</div><div class="ttdoc">the original cloud the Host</div><div class="ttdef"><b>Definition:</b> gpu_extract_clusters.h:141</div></div>
<div class="ttc" id="aclasspcl_1_1gpu_1_1_euclidean_cluster_extraction_html_a6b53d0688720222882181e18967ca731"><div class="ttname"><a href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a6b53d0688720222882181e18967ca731">pcl::gpu::EuclideanClusterExtraction::cluster_tolerance_</a></div><div class="ttdeci">double cluster_tolerance_</div><div class="ttdoc">The spatial cluster tolerance as a measure in the L2 Euclidean space.</div><div class="ttdef"><b>Definition:</b> gpu_extract_clusters.h:147</div></div>
<div class="ttc" id="aclasspcl_1_1gpu_1_1_euclidean_cluster_extraction_html_a81a359b0267f431fe49e3a8ce69548b7"><div class="ttname"><a href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a81a359b0267f431fe49e3a8ce69548b7">pcl::gpu::EuclideanClusterExtraction::min_pts_per_cluster_</a></div><div class="ttdeci">int min_pts_per_cluster_</div><div class="ttdoc">The minimum number of points that a cluster needs to contain in order to be considered valid (default...</div><div class="ttdef"><b>Definition:</b> gpu_extract_clusters.h:150</div></div>
<div class="ttc" id="aclasspcl_1_1gpu_1_1_euclidean_cluster_extraction_html_ac16cba791c7693efe0c0f62ca753d775"><div class="ttname"><a href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#ac16cba791c7693efe0c0f62ca753d775">pcl::gpu::EuclideanClusterExtraction::max_pts_per_cluster_</a></div><div class="ttdeci">int max_pts_per_cluster_</div><div class="ttdoc">The maximum number of points that a cluster needs to contain in order to be considered valid (default...</div><div class="ttdef"><b>Definition:</b> gpu_extract_clusters.h:153</div></div>
<div class="ttc" id="aclasspcl_1_1gpu_1_1_euclidean_cluster_extraction_html_afa283395168a4d277abf9190c9d536aa"><div class="ttname"><a href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#afa283395168a4d277abf9190c9d536aa">pcl::gpu::EuclideanClusterExtraction::tree_</a></div><div class="ttdeci">GPUTreePtr tree_</div><div class="ttdoc">A pointer to the spatial search object.</div><div class="ttdef"><b>Definition:</b> gpu_extract_clusters.h:144</div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#a4517e73e5d5530cf69d1e1a5f8ca6918">&#9670;&nbsp;</a></span>getSearchMethod()</h2>

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<p>Get a pointer to the search method used. </p>
<dl class="todo"><dt><b><a class="el" href="todo.html#_todo000022">待办事项:</a></b></dt><dd>fix this for a generic search tree </dd></dl>
<div class="fragment"><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;{ <span class="keywordflow">return</span> (<a class="code" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#afa283395168a4d277abf9190c9d536aa">tree_</a>); }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#a292d2bc70907745884b5e15a7ffd61f4">&#9670;&nbsp;</a></span>setClusterTolerance()</h2>

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          <td class="paramtype">double&#160;</td>
          <td class="paramname"><em>tolerance</em></td><td>)</td>
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<p>Set the spatial cluster tolerance as a measure in the L2 Euclidean space </p>
<dl class="params"><dt>参数</dt><dd>
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    <tr><td class="paramname">tolerance</td><td>the spatial cluster tolerance as a measure in the L2 Euclidean space </td></tr>
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<div class="fragment"><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;{ <a class="code" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a6b53d0688720222882181e18967ca731">cluster_tolerance_</a> = tolerance; }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#a7e03de53c8b6b1e8e43454177da35eba">&#9670;&nbsp;</a></span>setMaxClusterSize()</h2>

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          <td class="paramname"><em>max_cluster_size</em></td><td>)</td>
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<p>Set the maximum number of points that a cluster needs to contain in order to be considered valid. </p>
<dl class="params"><dt>参数</dt><dd>
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    <tr><td class="paramname">max_cluster_size</td><td>the maximum cluster size </td></tr>
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  </dd>
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<div class="fragment"><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;{ <a class="code" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#ac16cba791c7693efe0c0f62ca753d775">max_pts_per_cluster_</a> = max_cluster_size; }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#a232fc7f0877a4dd40131471f1c8164b6">&#9670;&nbsp;</a></span>setMinClusterSize()</h2>

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          <td class="paramtype">int&#160;</td>
          <td class="paramname"><em>min_cluster_size</em></td><td>)</td>
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<p>Set the minimum number of points that a cluster needs to contain in order to be considered valid. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramname">min_cluster_size</td><td>the minimum cluster size </td></tr>
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<div class="fragment"><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;{ <a class="code" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#a81a359b0267f431fe49e3a8ce69548b7">min_pts_per_cluster_</a> = min_cluster_size; }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#a95c549e9549f86d19df8abfbcac0add6">&#9670;&nbsp;</a></span>setSearchMethod()</h2>

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          <td>(</td>
          <td class="paramtype">GPUTreePtr &amp;&#160;</td>
          <td class="paramname"><em>tree</em></td><td>)</td>
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<p>the destructor </p>
<p>Provide a pointer to the search object. </p><dl class="params"><dt>参数</dt><dd>
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    <tr><td class="paramname">tree</td><td>a pointer to the spatial search object. </td></tr>
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<div class="fragment"><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;{ <a class="code" href="classpcl_1_1gpu_1_1_euclidean_cluster_extraction.html#afa283395168a4d277abf9190c9d536aa">tree_</a> = tree; }</div>
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<hr/>该类的文档由以下文件生成:<ul>
<li>gpu/segmentation/include/pcl/gpu/segmentation/<a class="el" href="gpu__extract__clusters_8h_source.html">gpu_extract_clusters.h</a></li>
<li>gpu/segmentation/include/pcl/gpu/segmentation/impl/<a class="el" href="gpu__extract__clusters_8hpp_source.html">gpu_extract_clusters.hpp</a></li>
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